Junfeng Luo
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
Papers in
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- Advanced Neural Network Applications 2
- Handwritten Text Recognition Techniques 1
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- Autonomous Vehicle Technology and Safety 1
- Co-authors
- Xiaoming Wei (2 shared papers)Xiaolin K. Wei (2 shared papers)Shenqi Lai (1 shared paper)Mingyuan Fan (1 shared paper)Zhenhua Chai (1 shared paper)Junshi Huang (1 shared paper)Jinming Su (1 shared paper)Ke Zhang (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)arXiv (Cornell University) (1 paper)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (1 paper)IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
- Partner nations
- China
In The Last Decade
Junfeng Luo
3 papers receiving 622 citations
Junfeng Luo's Hit Papers
Peers
Comparison fields: 5 of 32
- Computer Vision and Pattern Recognition 423
- Automotive Engineering 82
- Media Technology 57
- Industrial and Manufacturing Engineering 39
- Ocean Engineering 21
Countries citing papers authored by Junfeng Luo
This map shows the geographic impact of Junfeng Luo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Junfeng Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junfeng Luo more than expected).
Fields of papers citing papers by Junfeng Luo
This network shows the impact of papers produced by Junfeng Luo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Junfeng Luo. The network helps show where Junfeng Luo may publish in the future.
Co-authors
The 12 scholars most cited alongside Junfeng Luo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Rethinking BiSeNet For Real-time Semantic Segmentation Hit paper breakdown → | 2021 | 566 |
| 2 | 2021 | 69 | |
| 3 | 2026 | 1 | |
| 4 | 2025 | 0 |
About Junfeng Luo
Junfeng Luo is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 4 papers that have together received 636 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Autonomous Vehicle Technology and Safety (1 paper) and Handwritten Text Recognition Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (423 citations), Automotive Engineering (82 citations), Media Technology (57 citations), Industrial and Manufacturing Engineering (39 citations) and Ocean Engineering (21 citations). Junfeng Luo has collaborated with scholars based in China. Frequent co-authors include Xiaoming Wei, Xiaolin K. Wei, Shenqi Lai, Mingyuan Fan, Zhenhua Chai, Junshi Huang, Jinming Su, Ke Zhang, Xiaokang Yang and Jialin Gao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, arXiv (Cornell University), IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings and IEEE/CVF International Conference on Computer Vision (ICCV).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.